CV-long - Department of Knowledge-Based Mathematical Systems ...

Personal Data
Name: Edwin Lughofer
Date of Birth: August 4, 1972
Place of Birth: Ried i.I., Austria
Gender: Male
Nationality: Austrian
Marital Status: Married
Curriculum Vitae: Edwin Lughofer
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Education, Employment, Awards, Grants
1978–1982: Elementary School: Volksschule Riedberg, Austria
1982–1990: Secondary School: Bundesrealgymnasium Ried i.I.
10/1990–2/1997: Studies in Technical Mathematics at the Johannes Kepler Univer-
sität Linz, Austria
From 1997 on: Research assistant at the Institut für Wissensbasierte Mathematis-
che Systeme, Johannes Kepler Universität Linz
02/1997: Master degree in Technical Mathematics at the Johannes Kepler
Universität Linz, Austria (Diploma Thesis: ’Application of Math-
ematical Signal Analysis for Detecting Noise on Compact Discs’)
06/2005: PhD degree in Applied Mathematics at the Johannes Kepler Uni-
versität Linz, Austria (PhD Thesis: ’Data-Driven Incremental
Learning of Takagi-Sugeno Fuzzy Models’)
09/2006: Best paper award for the invited paper ’Process safety enhance-
ments for data-driven evolving fuzzy models’ at the International
Symposium on Evolving Fuzzy Systems 2006, Lake District
05/2007: Royal Society Grant for know-how exchange in data-driven evolv-
ing fuzzy systems with Lancaster University
03/2008: Best finalist paper award for the paper ’Applying Evolving Fuzzy
Models with Adaptive Local Error Bars to On-Line Fault Detec-
tion’ at the International Symposium on Genetic and Evolving
Fuzzy Systems 2008, Witten-Bommerholz, Germany
Specialized in: Data-driven modelling, evolving fuzzy systems, machine learning
(incremental learning), data mining (clustering), fault detection,
image processing and fuzzy control
URL: http://www.flll.jku.at/staff/edwin/
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Selected Projects
03/1995–03/1999: Noise Detector for Compact Discs (ND): automatic detection of
noise on Compact Discs through inspection of digital music curves
11/1997–04/2000: Fuzzy Controller for special Water Power Plants (KWR), Meta-
Controller for all Water Power Plants along the Danube (DSR)
2002-2004: Automatic Measurement Plausibility and Quality Assurance
(AMPA-EU Project)
2005-2010: DynaVis (EU-Project): Dynamically Reconfigurable Quality
Control for Manufacturing and Production Processes Using Learn-
ing Machine Vision: www.dynavis.org
SynTeX (EU-Project): Measuring Feelings and Expectations As-
sociated with Textures: www.syntex.or.at
ASHMOSD (National FFG Research Project, special Call in
’Aeronautics’): Austrian Structural Health Monitoring System
Demonstrator
Technology Transfer sponsored by the Upperaustrian technology
and research promotion
Exchange of know-how in data-driven evolving fuzzy systems
with Lancaster University, sponsored by the Royal Society Grant,
United Kingdom
FFG Research Project: Simulation-based steel bending control
ND new: MATLAB prototype for noise detection on analog tapes
2010/2011: PAC (K-Project): Process Analytical Chemistry - Data Acqui-
sition and Data Processing, national research project including 7
academic and 9 industrial partners, see http://www.k-pac.at/.
IREFS (FWF/DFG Lead Agency): Interpretable and Reliable
Evolving Fuzzy Systems - joint cooperation project with the In-
stitute for Computational Intelligence and Bioinformatics, Phillips
University Marburg
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Research Activities
Co-Organizer of the Special Issue ’On-line Fuzzy Machine Learning and Data Mining’ at
the ’Information Sciences’ journal (Elsevier).
Co-Organizer of the Special Sessions ’Learning in evolving environments and its appli-
cation on real-world problems’ at the ICMLA 2011 conference (Honolulu, Hawaii), ’On-
line Fuzzy Modeling and Pattern Recognition’ at the EUSFLAT 2011 conference (Aix-Les-
Bains), ’Dynamic Learning in Non-Stationary Environments’ at the ICMLA 2010 confer-
ence (Washington), ’Fuzzy Machine Learning and Data Mining’ at the IPMU 2010 confer-
ence (Dortmund), ’Recent Advances in Evolving Fuzzy Systems’ at the EUSFLAT/IFSA
2009 conference (Lissabon)
Member of the Editorial Board and Associate Editor of the International Journals on ’Evolv-
ing Systems’ (Springer) and ’Organizational and Collective Intelligence’
Member of the Programme Committee at the 6th International Conference on Soft Methods
in Probability and Statistics (SMPS 2012), the 9th International Conference on Fuzzy Sys-
tems and Knowledge Discovery (FSKD’12), the 2011 International Conference on Adaptive
and Intelligent Systems (ICAIS’11), the IEEE Workshop on Evolving and Adaptive Intelli-
gent Systems 2011 (EAIS’10) and of the International Symposium on Evolving Intelligent
Systems 2010 (EIS’10), International Conference on Informatics in Control, Automation
and Robotics (ISINCO) 2011, of the Special Session Multiple Model Approach to Machine
Learning (MMAML) 2011 and 2012, of the EUSFLAT/IFSA 2009 conference, of the 2009
IEEE Workshop on Evolving and Self-Developing Intelligent Systems and of the 8th In-
ternational Conference on Pervasive Intelligence and Computing (PICom 2009), Chengdu,
China
Member of the Working Group on Learning and Data Mining (Webpage http://idbis.ugr.es/dami/)
and the ETTC Task Force on Machine Learning
(Webpage http://www.uni-marburg.de/fb12/kebi/research/TFML?language_sync=1)
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Reviewer for the Journals IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems,
IEEE Transactions on Systems, Men and Cybernetics part B: Cybernetics, Pattern Recogni-
tion, Information Sciences, Int. Journal of Approximate Reasoning, International Journals
of Uncertainty, Fuzziness and Knowledge-Based Systems, Soft Computing, IEEE Transac-
tions on Neural Networks, IEEE Transactions on Evolutionary Computation, Advances of
Fuzzy Systems (Hindawi), European Journal of Operational Research and several interna-
tional conferences
Monography
Edwin Lughofer. Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications,
Springer Verlag, Berlin Heidelberg, 2011, ISBN: 978-3-642-18086-6,.
Book Chapters
1. E. Lughofer. Towards Robust Evolving Fuzzy Systems. book chapter in Evolving Intel-
ligent Systems - Methodologies and Applications, editors: Plamen Angelov, Dimitar Filev
and Nik Kasabov, John Wiley and Sons, pp. 87-126, 2010
2. E.P. Klement, E. Lughofer, J. Himmelbauer and B. Moser. Data-Driven and Knowledge-
Based Modelling. book chapter in Hagenberg Research, editors: Michael Affenzeller,
Bruno Buchberger, Alois Ferscha, Michael Haller, Tudor Jebelean, Erich Peter Klement,
Josef Kueng, Peter Paule, Birgit Proell, Wolfgang Schreiner, Gerhard Weiss, Roland Wag-
ner, Wolfram Woess, Robert Stubenrauch and Wolfgang Windsteiger. Springer Verlag, pp.
237-279, 2009
3. C. Eitzinger, J.E. Smith, E. Lughofer and D. Sannen. Lernfaehige Inspektionssysteme.
Automatisierungsatlas, SPS Magazin 2009, pp. 370-372.
Journal Papers
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1. E. Lughofer. A Dynamic Split-and-Merge Approach for Evolving Cluster Models. Evolving
Systems (special issue on dynamic clustering), to appear, 2012.
2. E. Lughofer. Human Inspired Evolving Machines - The Next Generation of Evolving
Intelligent Systems? IEEE SMC Newsletter, vol. 36, 2011.
3. E. Lughofer. Hybrid Active Learning for Reducing Annotation Effort of Operators at Clas-
sification Systems. Pattern Recognition, vol. 45 (2), pp. 884–896, 2011.
4. C. Cernuda, E. Lughofer, W. Maerzinger and J. Kasberger. NIR-based Quantification of
Process Parameters in Polyetheracrylat (PEA) Production using Flexible Non-linear Fuzzy
Systems. Chemometrics and Intelligent Laboratory Systems, vol. 109 (1), pp. 22–33, 2011.
5. E. Lughofer, B. Trawinski, K. Trawinski, O. Kempa and T. Lasota. On Employing Fuzzy
Modeling Algorithms for the Valuation of Residential Premises. Information Sciences, vol.
181 (23), pp. 5123–5142, 2011.
6. E. Lughofer, J.-L. Bouchot and A. Shaker. On-line Elimination of Local Redundancies in
Evolving Fuzzy Systems. Evolving Systems, vol. 2 (3), pp. 165-187, 2011.
7. E. Lughofer. On-line Incremental Feature Weighting in Evolving Fuzzy Classifiers. Fuzzy
Sets and Systems, vol 163 (1), pp. 1-23, 2011.
8. E. Lughofer, V. Macian, C. Guardiola and Erich Peter Klement. Identifying Static and
Dynamic Prediction Models for NOx Emissions with Evolving Fuzzy Systems. Applied
Soft Computing, vol. 11 (2), pp. 2487–2500, 2011.
9. E. Lughofer, P. Angelov. Handling Drifts and Shifts in On-Line Data Streams with Evolving
Fuzzy Systems Applied Soft Computing, vol. 11 (2), pp. 2057–2068, 2011.
10. S. Thumfart, R. Jacobs, E. Lughofer, C. Eitzinger, F. Cornelissen, W. Groissboeck, R.
Richter. Modelling Human Aesthetic Perception of Visual Textures ACM Transactions
on Applied Perception, in press, 2011.
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11. E. Lughofer and S. Kindermann. SparseFIS: Data-driven Learning of Fuzzy Systems with
Sparsity Constraints. IEEE Transactions on Fuzzy Systems, vol. 18 (2), pp. 396-411, 2010.
12. W. Groissboeck, E. Lughofer and S. Thumfart. Associating Visual Textures with Human
Perceptions using Genetic Algorithms. Information Sciences, vol. 180 (11), pp. 2065-2084,
2010.
13. E. Lughofer. On-line Evolving Image Classifiers and Their Application to Surface Inspec-
tion. Image and Vision Computing, Vol. 28 (7), pp. 1065-1079, 2010.
14. D. Sannen, E. Lughofer and H. van Brussel. Towards Incremental Classifier Fusion. Intel-
ligent Data Analysis, vol. 14(1), 2010, pp. 3–30.
15. C. Eitzinger, W. Heidl, E. Lughofer, S. Raiser, J.E. Smith, M.A. Tahir, D. Sannen and H.
van Brussel. Assessment of the Influence of Adaptive Components in Trainable Surface
Inspection Systems. Machine Vision and Applications, Vol. 21 (5), pp. 613-626, 2010.
16. S. Raiser, E. Lughofer, C. Eitzinger and J.E. Smith. Impact of Object Extraction Methods
on Classification Performance in Surface Inspection Systems. Machine Vision and Appli-
cations, vol. 21(5), pp. 627-641, 2010.
17. E. Lughofer, J.E. Smith, M.A. Tahir, P. Caleb-Solly, C. Eitzinger, D. Sannen and M. Nuttin.
Human-Machine Interaction Issues in Quality Control Based on On-Line Image Classifica-
tion. IEEE Transactions on Systems, Man and Cybernetics, part A: Systems and Humans,
vol. 39 (5), 2009, pp. 960-971.
18. P. Angelov, E. Lughofer and Xiaowei Zhou. Evolving Fuzzy Classifiers using Differ-
ent Model Architectures. Fuzzy Sets and Systems, vol.159 (23), pp. 3160-3182, 2008,
doi:10.1016/j.fss.2008.06.019
19. E. Lughofer. FLEXFIS: A Robust Incremental Learning Approach for Evolving TS Fuzzy
Models. IEEE Transactions on Fuzzy Systems, vol. 16 (4), pp. 1393-1410, 2008
20. E. Lughofer. Extensions of Vector Quantization for Incremental Clustering. Pattern Recog-
nition, vol. 41(3), pp. 995-1011, 2008
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21. E. Lughofer and C. Guardiola. On-Line Fault Detection with Data-Driven Evolving Fuzzy
Models. Control and Intelligent Systems, vol. 36 (2), pp. 307-317, 2008
22. P. Angelov and E. Lughofer. Data-Driven Evolving Fuzzy Systems using eTS and FLEX-
FIS: Comparative Analysis. International Journal of General Systems, vol. 37(01), pp. 45
- 67, 2008
23. P. Angelov, V. Giglio, C. Guardiola, E. Lughofer, and J. M. Luján. An approach to model-
based fault detection in industrial measurement systems with application to engine test
benches. Measurement Science and Technology, vol.17, pp. 1809–1818, 2006.
Submitted Manuscripts
1. E. Lughofer. Single-Pass Active Learning with Conflict and Ignorance. Evolving Systems,
submitted, 2012.
2. E. Lughofer and O. Buchtala. Reliable All-Pairs Evolving Fuzzy Classifiers. IEEE Trans-
actions on Fuzzy Systems, in revision, 2011.
3. W. Heidl, S. Thumfart, E. Lughofer, C. Eitzinger and E.P. Klement. Machine Learning
Based Analysis of Gender Differences in Visual Inspection Decision Making Information
Sciences, submitted, 2011.
4. M. Pratama, M.J. ER, R.J. Oentaryo, L. San, L. Zhai, E. Lughofer, X. Li and I. Arifin. A
Robust Data-driven Modeling for Enhanced Parsimonious Fuzzy Neural Network Neuro-
computing, submitted, 2011.
5. C. Cernuda, E. Lughofer, L. Suppan, T. Röder, W. Maerzinger and J. Kasberger. Evolving
Chemometric Models for Predicting Dynamic Process Parameters in Viscose Production.
Analytic Chimica Acta, in revision, 2012.
6. M. Pratama, D. Jiang, M. Negnechivetsky, E.M. Joo, P. Angelov, E. Lughofer and I. Arifim.
PANFIS: A novel Incremental Learning Machine. IEEE Transactions on Fuzzy Systems,
submitted, 2012.
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7. E. Lughofer. Flexible Fuzzy Inference Systems from Data Streams (FLEXFIS ++). In:
Learning in Non-Stationary Environments: Methdologies and Applications, editors: M.-S.
Mouchaweh, E. Lughofer. Springer Verlag, New York, 2012, submitted.
8. D. Sannen, J.-M. Papy, S. Vandenplas, E. Lughofer, and H. Van Brussel. Incremental
Classifier Fusion: Applications in Industrial Monitoring and Diagnostics. In: Learning in
Non-Stationary Environments: Methdologies and Applications, editors: M.-S. Mouchaweh,
E. Lughofer. Springer Verlag, New York, 2012, submitted.
9. E. Lughofer, C. Eitzinger and C. Guardiola. On-line Quality Control with Flexible Evolv-
ing Fuzzy Systems. In: Learning in Non-Stationary Environments: Methdologies and
Applications, editors: M.-S. Mouchaweh, E. Lughofer. Springer Verlag, New York, 2012,
submitted.
Research Visits, Stays
January and November 2011: Institute for Computational Intelligence and Bioinformatics,
Phillips University Marburg
August 2008: Fraunhofer Institute Techno- and Wirtschaftinformatik, University Kaiser-
slautern
January 2008: Institute for Computational Intelligence and Bioinformatics, Phillips Univer-
sity Marburg
November 2007: Center for Bioimage Informatics and Departments of Biological Sciences,
Biomedical Engineering, and Machine Learning Carnegie Mellon University, Pittsburgh,
Pennsylvania, U.S.A.
September 2006 and May 2007: Department of Communication Systems, InfoLab21, Lan-
caster University
January 2006: Faculty for Informatics (ITI), Otto-von-Guericke-University
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Some Invited Talks
1. Evolving Fuzzy Systems - An Overview, Institute of Measurement and Control Engineering,
University of Siegen (15th of November 2011)
2. Evolving Fuzzy Systems - Interpretability Aspects, Institute for Computational Intelligence
and Bioinformatics, Phillips University Marburg (13th of January 2011)
3. Evolving Fuzzy Systems - An Overview, Workshop Model Based Calibration Methods at
the Technical University of Vienna (17th of September 2010)
4. An Adaptive Image Classification Framework for On-Line Surface Inspection, Workshop at
QCAV 2009 conference, Wels, Austria (29th May 2009)
5. Workshop on Off-Line and On-Line Image Classification Framework for Surface Inspec-
tion, Fraunhofer Institut Techno- und Wirtschaftsmathematik, University Kaiserslautern
(29th of August 2008)
6. An On-Line Self-Adaptive and Interactive Image Classification Framework, Fachbereich
Mathematik und Informatik, Phillips University Marburg (17th of January 2008)
7. Components of an On-line Image Classification Framework, Center for Bio-image Infor-
matics and Department of Biological Sciences, Biomedical Engineering, and Machine Learn-
ing Carnegie Mellon University, Pittsburgh, Pennsylvania, U.S.A. (14th of November 2007)
8. Model-Based On-Line Fault Detection and Image Classification, InfoLab21, University of
Lancaster (24th of May 2007)
9. Data-Driven Evolving Fuzzy Models, InfoLab21, University of Lancaster (12. September
2006)
10. Process safety enhancements for data-driven evolving fuzzy models, EFS06 conference,
Lake District, Lancaster (7-9th of September 2006)
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11. Data-Driven Evolving Fuzzy Models - Algorithms and Applications, Otto von Guericke
Universität Magdeburg (12.01.2006) - Algorithms and Advanced Aspects for Interpretabil-
ity and Process Safety Enhancements,
Conference Papers
1. E. Lughofer. Dynamic Evolving Cluster Models Using Split-and-Merge Operations. Pro-
ceedings of the ICMLA 2011, pp. 20–26, 2011.
2. E. Lughofer, All-Pairs Evolving Fuzzy Classifiers for On-line Multi-Class Classification
Problems, Proceedings of the EUSFLAT 2011 conference, Aix-Les-Bains, France, pp. 372-
379, 2011.
3. E. Lughofer and E. Hüllermeier, On-line Redundancy Elimination in Evolving Fuzzy Re-
gression Models using a Fuzzy Inclusion Measure, Proceedings of the EUSFLAT 2011
conference, Aix-Les-Bains, France, pp. 380-387, 2011.
4. M. Nasiri, E. Hüllermeier, R. Senge and E. Lughofer, Comparing Methods for Knowledge-
Driven and Data-Driven Fuzzy Modeling: A Case Study in Textile Industry, IFSA World
Congress 2011, Surabaya and Bali Islands, Indonesia.
5. E. Lughofer, B. Trawinski, K. Trawinski, O. Kempa, T. Lasota. On-line Valuation of
Residential Premises with Evolving Fuzzy Models. Proceedings of the Hybrid Artificial
Intelligence Systems Conference, HAIS 2011, Wroclaw, Poland, pp. 107-115.
6. B. Trawiñski, K. Trawiñski, E. Lughofer and T. Lasota. Investigation of Evolving Fuzzy
Systems Methods FLEXFIS and eTS on Predicting Residential Prices. Proceedings of the
9th International Workshop in Fuzzy Logic and Applications (WILF) 2011, Trani, Italy, pp.
123–130.
7. W. Heidl, S. Thumfart, C. Eitzinger, E. Lughofer, E.P. Klement. Decision Tree-Based
Analysis Suggests Structural Gender Differences in Visual Inspection. Proceedings of the
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IASTED Artificial Intelligence and Applications (AIA) Conference 2011, Innsbruck, Austria,
pp. 142–149, 2011.
8. E. Lughofer. On Dynamic Selection of the Most Informative Samples in Classification
Problems. Proc. International Conference on Machine Learning and Applications (ICMLA)
2010, Washington DC, pp. 573–579, 2010.
9. W. Heidl, S. Thumfart, E. Lughofer, C. Eitzinger, E.P. Klement. Classifier-Based Anal-
ysis of Visual Inspection: Gender Differences in Decision-Making Proceedings of IEEE
Conference on Systems, Man and Cybernetics, SMC 2010, pp. 113-120, Istanbul, 2010.
10. E. Lughofer. On Dynamic Soft Dimension Reduction in Evolving Fuzzy Classifiers. Proc.
of the 13th International Conference on Information Processing and Management of Un-
certainty (IPMU) 2010, LNAI, vol. 6178, Springer, pp. 79–88, Dortmund, Germany, 2010.
11. E. Lughofer, V. Macian, C. Guardiola, E.P. Klement. Data-Driven Design of Takagi-Sugeno
Fuzzy Systems for Predicting NOx Emissions. Proc. of the 13th International Conference
on Information Processing and Management of Uncertainty, IPMU 2010, Part II (Appli-
cations), Communication in Computer and Information Science, CCIS 81, pp. 1-10, Dort-
mund, 2010.
12. D. Sannen, E. Lughofer, H. van Brussel. Boosting Online Classification Performance Using
Incremental Classifier Fusion. Proceedings of the International Conference on Adaptive
and Intelligent Systems (ICAIS), Klagenfurt, Austria, 2009, pp. 101-107.
13. E. Lughofer and S. Kindermann. Rule Weight Optimization and Feature Selection in Fuzzy
Systems with Sparsity Constraints. Proc. of the Proceedings of the IFSA/EUSFLAT 2009
conference, Lisbon, Portugal, 2009, pp. 950-956.
14. E. Lughofer and P. Angelov. Detecting and Reacting on Drifts and Shifts in Online Data
Streams with Evolving Fuzzy Systems. Proc. of the Proceedings of the IFSA/EUSFLAT
2009 conference, Lisbon, Portugal, 2009, pp. 931-937.
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15. E. Lughofer and R. Richter. An Adaptive Image Classification Framework for On-Line
Surface Inspection. to appear in the Proc. of the QCAV (Quality Control by Artificial
Vision) 2009 conference, Wels, Austria, 2009.
16. E. Lughofer, J.E. Smith, M.A. Tahir, P. Caleb-Solly, C. Eitzinger, D. Sannen, H. van Brus-
sels. On Human-Machine Interaction During Online Image Classifier Training. in Proc.
of the International Conference on Computational Intelligence for Modelling, Control and
Automation (CIMCA), pp. 995-1001, Vienna, 2008.
17. E. Lughofer. Evolving Vector Quantization for Classification of On-Line Data Streams. in
Proc. of the International Conference on Computational Intelligence for Modelling, Control
and Automation (CIMCA), pp. 780-786, Vienna, 2008.
18. H. Schoener, B. Moser and E. Lughofer. On Preprocessing Multi-Channel Data for Online
Process Monitoring. in Proc. of the International Conference on Computational Intelli-
gence for Modelling, Control and Automation (CIMCA), pp. 414-420, Vienna, 2008.
19. E. Lughofer and S. Kindermann. Improving the Robustness of Data-Driven Fuzzy Systems
with Regularization. in Proc. of the IEEE World Congress on Computational Intelligence
(WCCI) 2008, pp. 703-709, Hongkong, 2008
20. C. Eitzinger, M. Gmainer, W. Heidl and E. Lughofer. Increasing Classification Robustness
with Adaptive Features. in International Conference on Computer Vision Systems 2008,
A. Gasteratos, M. Vincze, J.K. Tsotsos (Eds.), Springer Lecture Notes 5008, pp. 445-453,
Santorini Island, Greece
21. D. Sannen, M. Nuttin, J.E. Smith, M.A. Tahir, P. Caleb-Solly, E. Lughofer, C. Eitzinger.
An On-Line Self-Adaptive and Interactive Image Classification Framework. in Interna-
tional Conference on Computer Vision Systems 2008, A. Gasteratos, M. Vincze, J.K. Tsotsos
(Eds.), Springer Lecture Notes 5008, pp. 171-180, Santorini Island, Greece
22. E. Lughofer and C. Guardiola. Applying Evolving Fuzzy Models with Adaptive Local Error
Bars to On-Line Fault Detection. to appear in 3rd International Workshop on Genetic and
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Evolving Fuzzy Systems, GEFS 2008, pp. 35–40, Witten-Bommerholz (Germany), 2008
23. E. Lughofer, P. Angelov and X. Zhou. Evolving single- and multi-model fuzzy classifiers
with FLEXFIS-CLASS. in Proceedings of FUZZ-IEEE 2007, pp. 363-368, London, UK,
2007
24. P. Angelov, X, Zhou, E. Lughofer and D. Filev. Architectures for evolving fuzzy rule-based
classifiers. in Proc. Systems, Man and Cybernetics conference (SMC) 2007, pp. 2050-2055,
Montreal, Canada, 2007
25. E. Lughofer. Process safety enhancements for data-driven evolving fuzzy models. In
Proceedings of the International Symposium on Evolving Fuzzy Systems,pp. 42–48, Lake
District, UK, 2006 (awarded as best paper)
26. J. Botzheim, E. Lughofer, E.P. Klement, L. Kóczy, and T.D. Gedeon. Separated antecedent
and consequent learning for takagi-sugeno fuzzy systems. In Proceedings of FUZZ-IEEE
2006, Vancouver, Canada, 2006.
27. E. Lughofer and U. Bodenhofer. Incremental learning of fuzzy basis function networks
with a modified version of vector quantization. In Proceedings of IPMU 2006, pp. 56–63,
Paris, France, 2006.
28. E. Lughofer, E. Hüllermeier, and E.P. Klement. Improving the interpretability of data-driven
evolving fuzzy systems. In Proceedings of EUSFLAT 2005, pages 28–33, Barcelona, Spain,
2005.
29. E. Lughofer and E.P. Klement. FLEXFIS: A variant for incremental learning of Takagi-
Sugeno fuzzy systems. In Proceedings of FUZZ-IEEE 2005, pages 915–920, Reno, Nevada,
U.S.A., 2005.
30. P. Angelov, E. Lughofer, and E.P. Klement. Two approaches to data-driven design of
evolving fuzzy systems: ETS and FLEXFIS. In Proceedings of NAFIPS 2005, Ann Arbor,
Michigan, U.S.A., 2005.
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31. W. Groißböck, E. Lughofer, and E.P. Klement. A comparison of variable selection methods
with the main focus on orthogonalization. In M. Lopéz-Díaz, M. Á. Gil, P. Grzegorzewski,
O. Hryniewicz, J. Lawry (Eds.), Soft Methodology and Random Information Systems, Ad-
vances in Soft Computing, Springer, Berlin, Heidelberg, New York, pp. 479–486, 2004.
32. E. Lughofer and E.P. Klement. Premise parameter estimation and adaptation in fuzzy
systems with open-loop clustering methods. In Proceedings of FUZZ-IEEE 2004, Budapest,
Hungary, 2004.
33. E. Lughofer, E.P. Klement, J.M. Lujan, and C. Guardiola. Model-based fault detection
in multi-sensor measurement systems. In Proceedings of IEEE IS 2004, pages 184–189,
Varna, Bulgaria, 2004.
34. J. Galindo, J.M. Lujan, C. Guardiola, E. Lughofer, and E.P. Klement. Fault detection in
engine measurement systems by a model-based approach. In Proc. SAE 2004. SAE, 2004.
35. E. Lughofer, H. Efendic, L. Del Re, and E.P. Klement. Filtering of dynamic measurements
in intelligent sensors for fault detection based on data-driven models. In Proceedings IEEE
CDC — IEEE CDC Conference, Maui, Hawaii, pages 463–468, 2003.
36. E. Lughofer and E.P. Klement. Online adaptation of Takagi-Sugeno fuzzy inference sys-
tems. In Proceedings of CESA’2003—IMACS Multiconference, Lille, France, 2003. CD-
Rom, paper S1-R-00-0175.
37. A. Schrempf, L. Del Re, W. Groißböck, E. Lughofer, E.P. Klement, and G. Frizberg. Auto-
matic engine modelling for failure detection. In Proc. 2001 ASME International Mechani-
cal Engineering Congress and Exposition, 2001.
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